Senior AI/ML Data Scientist

Job Description

The role ensures models are accurate, reliable, and aligned with business objectives, while translating complex business requirements into actionable AI solutions and promoting transparency across key processes and performance indicators.

Our client based in Dubai, is one of the largest semi-government organisations in the region. This position is a contract role with an initial duration of 15 months and is renewable.

Key Responsibilities:

• Design, train, validate, and deploy advanced ML/DL models (NLP, CV, transformers, statistical learning).
• Optimize models for accuracy, scalability, and latency to ensure production readiness.
• Apply responsible AI principles, including fairness, bias detection, and explainability.
• Build and manage pipelines, feature stores, and ingestion frameworks (real-time and batch).
• Implement MLOps practices: CI/CD workflows, registries, automated retraining, and observability.
• Monitor and resolve issues related to data drift, leakage, and model reliability.
• Ensure compliance with GDPR, ISO standards, ICAO digital/AI frameworks, and organizational policies.
• Promote transparency of AI-driven KPIs and processes across the enterprise.
• Conduct fairness audits, model explainability, and ethical risk assessments.
• Translate complex, ambiguous business challenges into AI/ML opportunities.
• Define scope, feasibility, and expected value of AI initiatives.
• Advise stakeholders on risks, trade-offs, and adoption strategies.
• Deliver insights, dashboards, and validation reports to senior management and cross-functional teams.
• Influence adoption of AI solutions using expert authority and evidence-based recommendations.
• Act as a subject matter expert, supporting enterprise-wide AI strategy and operational decisions.

Knowledge, skills & experience:

• Professional certification in Machine Learning (preferred).
• Bachelor&aposs degree in Computer Science, Mathematics, Statistics, Data Science, or related
• Proven experience applying AI/ML solutions in real-world domains.
• Strong track record in translating business challenges into AI/ML opportunities with measurable business impact.
• Expertise in deep learning and statistical methods, with hands-on model development and production deployment.
• Familiarity with responsible AI principles and their application in regulated industries.
• Programming & Data Science: Python, R, SQL, StreamLit
• ML & AI Frameworks: TensorFlow, PyTorch, Keras, scikit-learn, Hugging Face
• MLOps & Deployment: Docker, Kubernetes, Git CI/CD
• Data Engineering: Apache Spark, Kafka, dbt
• Cloud Platforms: Azure ML
• Visualization: Power BI, Tableau
• Responsible AI Tools: AI Governance Platform (e.g. Atlan)